code: def test_dataframe_quantile_execution(setup):
      raw = pd.DataFrame(
          {
              "a": np.random.rand(10),
              "b": np.random.randint(1000, size=10),
              "c": np.random.rand(10),
              "d": [np.random.bytes(10) for _ in range(10)],
              "e": [pd.Timestamp(f"201{i}") for i in range(10)],
              "f": [pd.Timedelta(f"{i} days") for i in range(10)],
          },
          index=pd.RangeIndex(1, 11),
      )
      df = DataFrame(raw, chunk_size=3)
  
      # q = 0.5, axis = 0, series
      r = df.quantile()
      result = r.execute().fetch()
      expected = raw.quantile()
  
      pd.testing.assert_series_equal(result, expected)
  
      # q = 0.5, axis = 1, series
      r = df.quantile(axis=1)
      result = r.execute().fetch()
      expected = raw.quantile(axis=1)
  
      pd.testing.assert_series_equal(result, expected)
  
      # q is a list, axis = 0, dataframe
      r = df.quantile([0.3, 0.7])
      result = r.execute().fetch()
      expected = raw.quantile([0.3, 0.7])
  
      pd.testing.assert_frame_equal(result, expected)
  
      # q is a list, axis = 1, dataframe
      r = df.quantile([0.3, 0.7], axis=1)
      result = r.execute().fetch()
      expected = raw.quantile([0.3, 0.7], axis=1)
  
      pd.testing.assert_frame_equal(result, expected)
  
      # test interpolation
      r = df.quantile([0.3, 0.7], interpolation="midpoint")
      result = r.execute().fetch()
      expected = raw.quantile([0.3, 0.7], interpolation="midpoint")
  
      pd.testing.assert_frame_equal(result, expected)
  
      q = tensor([0.3, 0.7])
  
      # q is a tensor
      r = df.quantile(q)
      result = r.execute().fetch()
      expected = raw.quantile([0.3, 0.7])
  
      pd.testing.assert_frame_equal(result, expected)
  
      # test numeric_only
      raw2 = pd.DataFrame(
          {
              "a": np.random.rand(10),
              "b": np.random.randint(1000, size=10),
              "c": np.random.rand(10),
              "d": [pd.Timestamp(f"201{i}") for i in range(10)],
          },
          index=pd.RangeIndex(1, 11),
      )
      df2 = DataFrame(raw2, chunk_size=3)
  
      r = df2.quantile([0.3, 0.7], numeric_only=False)
      result = r.execute().fetch()
      expected = raw2.quantile([0.3, 0.7], numeric_only=False)
  
      pd.testing.assert_frame_equal(result, expected)
  
      r = df2.quantile(numeric_only=False)
      result = r.execute().fetch()
      expected = raw2.quantile(numeric_only=False)
  
      pd.testing.assert_series_equal(result, expected)
  
file_path: mars/mars/dataframe/statistics/tests/test_statistics_execution.py
imports: import numpy
  import pandas
  import pytest
  from ....tensor import tensor
  from ...None import Series, DataFrame
label_desc: Use image node_id 2 for calling a global function with example usage: test_dataframe_quantile_execution(setup) without return types